A number of techniques are known to those of skill in the art for generating query reports. Specifically, in the field of on-line advertising, query reports representative of the number of “clicks” of on-line advertisements corresponding to a search query, are regularly sent to advertisers. Advertisers may use these query reports to determine keywords upon which to place bids, to improve the content of advertisements, and to improve relevance of advertisements to keywords. Similarly, search providers may use query reports to develop potential bidding keywords, to suggest new advertisements groups based upon end-user feedback (which is determined from click rates) and to improve relevance through the feedback of end-users.
Analysis of these query reports, however, requires humans to engage in a tedious interaction with a given query report to locate unique or interesting search queries. Search providers typically use unique or interesting search queries to better understand end user queries and thereby improve relevance and develop new potential bidding keywords that may be sold to advertisers. Similarly, advertisers use unique or interesting search queries in order to determine keywords upon which to bid and to improve the content of advertisements. The process of manually identifying unique or interesting keywords, however, does not guarantee accuracy or comprehensiveness. As such, both advertisers and search providers experience unreliable and incomplete performance in their analysis of search queries and, therefore, there exists a need for improved methods, systems and computer program products for generating structured search query reports.